Volunteer Summary

CONSORT Flow Diagram

Overall status

Characteristic

Overall1

Control1

Treatment1

time_point

1st

78

39

39

2nd

60

33

27

1n

Demographic information

Characteristic

N

Overall, N = 781

control, N = 391

treatment, N = 391

p-value2

age

78

41.15 ± 18.34 (21 - 148)

42.47 ± 21.27 (22 - 148)

39.82 ± 15.00 (21 - 70)

0.526

gender

78

0.202

female

57 (73%)

26 (67%)

31 (79%)

male

21 (27%)

13 (33%)

8 (21%)

occupation

78

0.831

civil

3 (3.8%)

2 (5.1%)

1 (2.6%)

clerk

15 (19%)

7 (18%)

8 (21%)

homemaker

7 (9.0%)

2 (5.1%)

5 (13%)

manager

10 (13%)

6 (15%)

4 (10%)

other

10 (13%)

4 (10%)

6 (15%)

professional

11 (14%)

8 (21%)

3 (7.7%)

retired

3 (3.8%)

1 (2.6%)

2 (5.1%)

service

4 (5.1%)

2 (5.1%)

2 (5.1%)

student

13 (17%)

6 (15%)

7 (18%)

unemploy

2 (2.6%)

1 (2.6%)

1 (2.6%)

working_status

78

53 (68%)

29 (74%)

24 (62%)

0.225

marital

78

>0.999

divorced

3 (3.8%)

1 (2.6%)

2 (5.1%)

married

21 (27%)

11 (28%)

10 (26%)

single

53 (68%)

26 (67%)

27 (69%)

widowed

1 (1.3%)

1 (2.6%)

0 (0%)

marital_r

78

>0.999

married

21 (27%)

11 (28%)

10 (26%)

other

4 (5.1%)

2 (5.1%)

2 (5.1%)

single

53 (68%)

26 (67%)

27 (69%)

education

78

0.040

primary

0 (0%)

0 (0%)

0 (0%)

secondary

11 (14%)

2 (5.1%)

9 (23%)

post-secondary

13 (17%)

9 (23%)

4 (10%)

university

54 (69%)

28 (72%)

26 (67%)

university_edu

78

54 (69%)

28 (72%)

26 (67%)

0.624

family_income

78

0.379

0_10000

10 (13%)

4 (10%)

6 (15%)

10001_20000

16 (21%)

5 (13%)

11 (28%)

20001_30000

13 (17%)

8 (21%)

5 (13%)

30001_40000

10 (13%)

5 (13%)

5 (13%)

40000_above

29 (37%)

17 (44%)

12 (31%)

high_income

78

39 (50%)

22 (56%)

17 (44%)

0.258

religion

78

0.605

buddhism

5 (6.4%)

4 (10%)

1 (2.6%)

catholic

5 (6.4%)

2 (5.1%)

3 (7.7%)

christianity

26 (33%)

12 (31%)

14 (36%)

nil

40 (51%)

21 (54%)

19 (49%)

other

1 (1.3%)

0 (0%)

1 (2.6%)

taoism

1 (1.3%)

0 (0%)

1 (2.6%)

religion_r

78

0.792

christianity

31 (40%)

14 (36%)

17 (44%)

nil

40 (51%)

21 (54%)

19 (49%)

other

7 (9.0%)

4 (10%)

3 (7.7%)

source

78

0.008

bokss

35 (45%)

14 (36%)

21 (54%)

facebook

12 (15%)

10 (26%)

2 (5.1%)

instagram

5 (6.4%)

5 (13%)

0 (0%)

other

12 (15%)

4 (10%)

8 (21%)

refresh

14 (18%)

6 (15%)

8 (21%)

1Mean ± SD (Range); n (%)

2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test

Measurement

Characteristic

N

Overall, N = 781

control, N = 391

treatment, N = 391

p-value2

sets

78

19.56 ± 2.28 (15 - 25)

19.18 ± 2.14 (15 - 24)

19.95 ± 2.38 (15 - 25)

0.138

setv

78

11.22 ± 1.70 (8 - 15)

11.03 ± 1.63 (8 - 14)

11.41 ± 1.77 (8 - 15)

0.322

maks

78

44.71 ± 3.70 (36 - 54)

44.26 ± 3.65 (36 - 52)

45.15 ± 3.74 (38 - 54)

0.287

ibs

78

15.64 ± 2.22 (9 - 20)

15.62 ± 2.14 (11 - 20)

15.67 ± 2.33 (9 - 20)

0.920

ers_e

78

12.32 ± 1.42 (9 - 15)

12.33 ± 1.46 (9 - 15)

12.31 ± 1.40 (9 - 15)

0.937

ers_r

78

11.41 ± 1.51 (8 - 15)

11.33 ± 1.36 (8 - 14)

11.49 ± 1.65 (8 - 15)

0.655

pss_pa

78

45.05 ± 4.65 (30 - 54)

44.41 ± 4.59 (30 - 54)

45.69 ± 4.68 (31 - 54)

0.226

pss_ps

78

25.33 ± 7.29 (12 - 42)

26.51 ± 7.71 (14 - 42)

24.15 ± 6.74 (12 - 41)

0.154

pss

78

43.28 ± 11.17 (21 - 72)

45.10 ± 11.69 (23 - 72)

41.46 ± 10.46 (21 - 67)

0.151

rki_responsible

78

21.21 ± 3.93 (13 - 29)

20.82 ± 4.25 (13 - 29)

21.59 ± 3.58 (14 - 28)

0.390

rki_nonlinear

78

13.45 ± 2.74 (7 - 22)

13.21 ± 2.48 (7 - 20)

13.69 ± 2.98 (8 - 22)

0.436

rki_peer

78

20.49 ± 2.20 (16 - 25)

20.54 ± 2.22 (16 - 25)

20.44 ± 2.20 (16 - 25)

0.838

rki_expect

78

4.69 ± 1.00 (3 - 7)

4.46 ± 0.94 (3 - 6)

4.92 ± 1.01 (3 - 7)

0.040

rki

78

59.83 ± 5.82 (50 - 80)

59.03 ± 5.89 (50 - 76)

60.64 ± 5.71 (50 - 80)

0.222

raq_possible

78

15.58 ± 1.89 (12 - 20)

15.64 ± 2.03 (12 - 20)

15.51 ± 1.76 (12 - 20)

0.767

raq_difficulty

78

12.31 ± 1.45 (9 - 15)

12.44 ± 1.48 (9 - 15)

12.18 ± 1.43 (9 - 15)

0.439

raq

78

27.88 ± 3.06 (21 - 35)

28.08 ± 3.26 (21 - 35)

27.69 ± 2.88 (21 - 35)

0.582

who

78

15.10 ± 4.32 (7 - 25)

14.95 ± 4.29 (8 - 25)

15.26 ± 4.41 (7 - 25)

0.756

phq

78

3.46 ± 3.65 (0 - 18)

3.72 ± 3.68 (0 - 14)

3.21 ± 3.65 (0 - 18)

0.539

gad

78

3.04 ± 3.13 (0 - 12)

3.28 ± 3.14 (0 - 12)

2.79 ± 3.15 (0 - 12)

0.496

nb_pcs

78

50.72 ± 7.81 (25 - 63)

51.43 ± 7.63 (25 - 63)

50.01 ± 8.03 (27 - 61)

0.428

nb_mcs

78

50.98 ± 8.68 (22 - 70)

50.39 ± 9.06 (22 - 68)

51.57 ± 8.36 (35 - 70)

0.553

1Mean ± SD (Range)

2Two Sample t-test

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

sets

(Intercept)

19.2

0.337

18.5, 19.8

group

control

—

—

—

treatment

0.769

0.477

-0.166, 1.70

0.110

time_point

1st

—

—

—

2nd

-0.321

0.405

-1.11, 0.473

0.431

group * time_point

treatment * 2nd

-0.034

0.595

-1.20, 1.13

0.954

Pseudo R square

0.038

setv

(Intercept)

11.0

0.272

10.5, 11.6

group

control

—

—

—

treatment

0.385

0.384

-0.368, 1.14

0.319

time_point

1st

—

—

—

2nd

0.255

0.274

-0.282, 0.791

0.356

group * time_point

treatment * 2nd

-0.182

0.404

-0.974, 0.610

0.654

Pseudo R square

0.011

maks

(Intercept)

44.3

0.624

43.0, 45.5

group

control

—

—

—

treatment

0.897

0.883

-0.833, 2.63

0.312

time_point

1st

—

—

—

2nd

0.043

0.501

-0.939, 1.03

0.931

group * time_point

treatment * 2nd

0.374

0.743

-1.08, 1.83

0.616

Pseudo R square

0.019

ibs

(Intercept)

15.6

0.339

15.0, 16.3

group

control

—

—

—

treatment

0.051

0.480

-0.889, 0.991

0.915

time_point

1st

—

—

—

2nd

0.190

0.323

-0.443, 0.824

0.559

group * time_point

treatment * 2nd

0.270

0.478

-0.666, 1.21

0.573

Pseudo R square

0.008

ers_e

(Intercept)

12.3

0.228

11.9, 12.8

group

control

—

—

—

treatment

-0.026

0.323

-0.659, 0.608

0.937

time_point

1st

—

—

—

2nd

-0.524

0.189

-0.894, -0.154

0.007

group * time_point

treatment * 2nd

0.510

0.280

-0.038, 1.06

0.073

Pseudo R square

0.022

ers_r

(Intercept)

11.3

0.235

10.9, 11.8

group

control

—

—

—

treatment

0.154

0.333

-0.499, 0.806

0.645

time_point

1st

—

—

—

2nd

-0.154

0.259

-0.662, 0.355

0.556

group * time_point

treatment * 2nd

0.291

0.382

-0.458, 1.04

0.450

Pseudo R square

0.011

pss_pa

(Intercept)

44.4

0.730

43.0, 45.8

group

control

—

—

—

treatment

1.28

1.033

-0.742, 3.31

0.217

time_point

1st

—

—

—

2nd

-1.29

0.807

-2.87, 0.288

0.114

group * time_point

treatment * 2nd

-0.083

1.188

-2.41, 2.25

0.945

Pseudo R square

0.040

pss_ps

(Intercept)

26.5

1.164

24.2, 28.8

group

control

—

—

—

treatment

-2.36

1.646

-5.59, 0.867

0.155

time_point

1st

—

—

—

2nd

1.16

1.131

-1.06, 3.38

0.310

group * time_point

treatment * 2nd

-1.16

1.671

-4.44, 2.12

0.490

Pseudo R square

0.041

pss

(Intercept)

45.1

1.739

41.7, 48.5

group

control

—

—

—

treatment

-3.64

2.459

-8.46, 1.18

0.142

time_point

1st

—

—

—

2nd

2.46

1.647

-0.765, 5.69

0.140

group * time_point

treatment * 2nd

-1.13

2.434

-5.90, 3.64

0.644

Pseudo R square

0.044

rki_responsible

(Intercept)

20.8

0.588

19.7, 22.0

group

control

—

—

—

treatment

0.769

0.832

-0.862, 2.40

0.357

time_point

1st

—

—

—

2nd

0.026

0.616

-1.18, 1.23

0.967

group * time_point

treatment * 2nd

-0.321

0.908

-2.10, 1.46

0.725

Pseudo R square

0.008

rki_nonlinear

(Intercept)

13.2

0.454

12.3, 14.1

group

control

—

—

—

treatment

0.487

0.642

-0.771, 1.75

0.450

time_point

1st

—

—

—

2nd

-0.316

0.444

-1.19, 0.555

0.480

group * time_point

treatment * 2nd

0.499

0.656

-0.787, 1.78

0.450

Pseudo R square

0.017

rki_peer

(Intercept)

20.5

0.361

19.8, 21.2

group

control

—

—

—

treatment

-0.103

0.511

-1.10, 0.898

0.841

time_point

1st

—

—

—

2nd

0.020

0.364

-0.694, 0.734

0.957

group * time_point

treatment * 2nd

0.139

0.538

-0.914, 1.19

0.796

Pseudo R square

0.001

rki_expect

(Intercept)

4.46

0.154

4.16, 4.76

group

control

—

—

—

treatment

0.462

0.218

0.035, 0.888

0.036

time_point

1st

—

—

—

2nd

0.177

0.198

-0.211, 0.564

0.375

group * time_point

treatment * 2nd

-0.017

0.290

-0.585, 0.551

0.954

Pseudo R square

0.058

rki

(Intercept)

59.0

0.878

57.3, 60.7

group

control

—

—

—

treatment

1.62

1.242

-0.818, 4.05

0.196

time_point

1st

—

—

—

2nd

-0.103

0.919

-1.90, 1.70

0.911

group * time_point

treatment * 2nd

0.281

1.355

-2.38, 2.94

0.837

Pseudo R square

0.025

raq_possible

(Intercept)

15.6

0.291

15.1, 16.2

group

control

—

—

—

treatment

-0.128

0.412

-0.935, 0.678

0.756

time_point

1st

—

—

—

2nd

-0.308

0.313

-0.921, 0.304

0.328

group * time_point

treatment * 2nd

0.660

0.461

-0.243, 1.56

0.157

Pseudo R square

0.010

raq_difficulty

(Intercept)

12.4

0.232

12.0, 12.9

group

control

—

—

—

treatment

-0.256

0.329

-0.901, 0.388

0.437

time_point

1st

—

—

—

2nd

-0.017

0.222

-0.453, 0.419

0.940

group * time_point

treatment * 2nd

0.212

0.329

-0.433, 0.856

0.522

Pseudo R square

0.005

raq

(Intercept)

28.1

0.484

27.1, 29.0

group

control

—

—

—

treatment

-0.385

0.685

-1.73, 0.958

0.576

time_point

1st

—

—

—

2nd

-0.289

0.467

-1.21, 0.627

0.538

group * time_point

treatment * 2nd

0.869

0.690

-0.484, 2.22

0.213

Pseudo R square

0.005

who

(Intercept)

14.9

0.691

13.6, 16.3

group

control

—

—

—

treatment

0.308

0.978

-1.61, 2.22

0.754

time_point

1st

—

—

—

2nd

-0.233

0.569

-1.35, 0.882

0.684

group * time_point

treatment * 2nd

-0.098

0.843

-1.75, 1.55

0.908

Pseudo R square

0.002

phq

(Intercept)

3.72

0.558

2.62, 4.81

group

control

—

—

—

treatment

-0.513

0.789

-2.06, 1.03

0.518

time_point

1st

—

—

—

2nd

0.021

0.386

-0.735, 0.778

0.956

group * time_point

treatment * 2nd

0.020

0.573

-1.10, 1.14

0.972

Pseudo R square

0.005

gad

(Intercept)

3.28

0.510

2.28, 4.28

group

control

—

—

—

treatment

-0.487

0.721

-1.90, 0.926

0.501

time_point

1st

—

—

—

2nd

0.166

0.423

-0.664, 0.996

0.696

group * time_point

treatment * 2nd

0.199

0.627

-1.03, 1.43

0.752

Pseudo R square

0.006

nb_pcs

(Intercept)

51.4

1.202

49.1, 53.8

group

control

—

—

—

treatment

-1.41

1.700

-4.75, 1.92

0.407

time_point

1st

—

—

—

2nd

-0.541

0.895

-2.30, 1.21

0.548

group * time_point

treatment * 2nd

2.31

1.328

-0.292, 4.91

0.087

Pseudo R square

0.008

nb_mcs

(Intercept)

50.4

1.345

47.8, 53.0

group

control

—

—

—

treatment

1.18

1.902

-2.55, 4.90

0.538

time_point

1st

—

—

—

2nd

-0.177

1.253

-2.63, 2.28

0.888

group * time_point

treatment * 2nd

-0.786

1.853

-4.42, 2.85

0.673

Pseudo R square

0.004

1SE = Standard Error, CI = Confidence Interval

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.38) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.18 (95% CI [18.52, 19.84], t(132) = 56.83, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.77, 95% CI [-0.17, 1.70], t(132) = 1.61, p = 0.107; Std. beta = 0.36, 95% CI [-0.08, 0.80])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.11, 0.47], t(132) = -0.79, p = 0.428; Std. beta = -0.15, 95% CI [-0.53, 0.22])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-1.20, 1.13], t(132) = -0.06, p = 0.954; Std. beta = -0.02, 95% CI [-0.57, 0.53])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.03 (95% CI [10.49, 11.56], t(132) = 40.58, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.38, 95% CI [-0.37, 1.14], t(132) = 1.00, p = 0.317; Std. beta = 0.23, 95% CI [-0.22, 0.68])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.28, 0.79], t(132) = 0.93, p = 0.352; Std. beta = 0.15, 95% CI [-0.17, 0.47])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.18, 95% CI [-0.97, 0.61], t(132) = -0.45, p = 0.653; Std. beta = -0.11, 95% CI [-0.58, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.26 (95% CI [43.03, 45.48], t(132) = 70.88, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.90, 95% CI [-0.83, 2.63], t(132) = 1.02, p = 0.309; Std. beta = 0.23, 95% CI [-0.22, 0.68])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.94, 1.03], t(132) = 0.09, p = 0.931; Std. beta = 0.01, 95% CI [-0.24, 0.26])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.37, 95% CI [-1.08, 1.83], t(132) = 0.50, p = 0.615; Std. beta = 0.10, 95% CI [-0.28, 0.47])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 7.80e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.62 (95% CI [14.95, 16.28], t(132) = 46.05, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.05, 95% CI [-0.89, 0.99], t(132) = 0.11, p = 0.915; Std. beta = 0.02, 95% CI [-0.43, 0.48])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.44, 0.82], t(132) = 0.59, p = 0.556; Std. beta = 0.09, 95% CI [-0.21, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.67, 1.21], t(132) = 0.57, p = 0.571; Std. beta = 0.13, 95% CI [-0.32, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.33 (95% CI [11.89, 12.78], t(132) = 53.99, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-0.66, 0.61], t(132) = -0.08, p = 0.937; Std. beta = -0.02, 95% CI [-0.47, 0.43])
  • The effect of time point [2nd] is statistically significant and negative (beta = -0.52, 95% CI [-0.89, -0.15], t(132) = -2.78, p = 0.006; Std. beta = -0.37, 95% CI [-0.64, -0.11])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.51, 95% CI [-0.04, 1.06], t(132) = 1.82, p = 0.068; Std. beta = 0.36, 95% CI [-0.03, 0.75])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.47) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.33 (95% CI [10.87, 11.79], t(132) = 48.14, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.50, 0.81], t(132) = 0.46, p = 0.644; Std. beta = 0.11, 95% CI [-0.34, 0.56])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-0.66, 0.35], t(132) = -0.59, p = 0.554; Std. beta = -0.11, 95% CI [-0.46, 0.24])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.29, 95% CI [-0.46, 1.04], t(132) = 0.76, p = 0.447; Std. beta = 0.20, 95% CI [-0.32, 0.72])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.48) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.41 (95% CI [42.98, 45.84], t(132) = 60.83, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.28, 95% CI [-0.74, 3.31], t(132) = 1.24, p = 0.214; Std. beta = 0.28, 95% CI [-0.16, 0.72])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -1.29, 95% CI [-2.87, 0.29], t(132) = -1.60, p = 0.109; Std. beta = -0.28, 95% CI [-0.62, 0.06])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.08, 95% CI [-2.41, 2.25], t(132) = -0.07, p = 0.945; Std. beta = -0.02, 95% CI [-0.52, 0.49])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.51 (95% CI [24.23, 28.79], t(132) = 22.78, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -2.36, 95% CI [-5.59, 0.87], t(132) = -1.43, p = 0.152; Std. beta = -0.32, 95% CI [-0.76, 0.12])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.16, 95% CI [-1.06, 3.38], t(132) = 1.02, p = 0.306; Std. beta = 0.16, 95% CI [-0.14, 0.46])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.16, 95% CI [-4.44, 2.12], t(132) = -0.69, p = 0.488; Std. beta = -0.16, 95% CI [-0.60, 0.29])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 45.10 (95% CI [41.70, 48.51], t(132) = 25.94, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -3.64, 95% CI [-8.46, 1.18], t(132) = -1.48, p = 0.139; Std. beta = -0.33, 95% CI [-0.77, 0.11])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 2.46, 95% CI [-0.77, 5.69], t(132) = 1.50, p = 0.135; Std. beta = 0.22, 95% CI [-0.07, 0.52])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.13, 95% CI [-5.90, 3.64], t(132) = -0.46, p = 0.642; Std. beta = -0.10, 95% CI [-0.54, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 8.24e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.82 (95% CI [19.67, 21.97], t(132) = 35.38, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.77, 95% CI [-0.86, 2.40], t(132) = 0.92, p = 0.355; Std. beta = 0.21, 95% CI [-0.24, 0.67])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-1.18, 1.23], t(132) = 0.04, p = 0.967; Std. beta = 7.18e-03, 95% CI [-0.33, 0.34])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.32, 95% CI [-2.10, 1.46], t(132) = -0.35, p = 0.724; Std. beta = -0.09, 95% CI [-0.59, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.21 (95% CI [12.32, 14.09], t(132) = 29.09, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.49, 95% CI [-0.77, 1.75], t(132) = 0.76, p = 0.448; Std. beta = 0.18, 95% CI [-0.28, 0.63])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.19, 0.55], t(132) = -0.71, p = 0.477; Std. beta = -0.11, 95% CI [-0.43, 0.20])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.79, 1.78], t(132) = 0.76, p = 0.447; Std. beta = 0.18, 95% CI [-0.28, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.55) and the part related to the fixed effects alone (marginal R2) is of 6.99e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.54 (95% CI [19.83, 21.25], t(132) = 56.89, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.10, 0.90], t(132) = -0.20, p = 0.841; Std. beta = -0.05, 95% CI [-0.49, 0.40])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.69, 0.73], t(132) = 0.05, p = 0.956; Std. beta = 8.92e-03, 95% CI [-0.31, 0.33])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-0.91, 1.19], t(132) = 0.26, p = 0.795; Std. beta = 0.06, 95% CI [-0.41, 0.53])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.30) and the part related to the fixed effects alone (marginal R2) is of 0.06. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.46 (95% CI [4.16, 4.76], t(132) = 28.99, p < .001). Within this model:

  • The effect of group [treatment] is statistically significant and positive (beta = 0.46, 95% CI [0.04, 0.89], t(132) = 2.12, p = 0.034; Std. beta = 0.47, 95% CI [0.04, 0.91])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.21, 0.56], t(132) = 0.89, p = 0.372; Std. beta = 0.18, 95% CI [-0.22, 0.58])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.58, 0.55], t(132) = -0.06, p = 0.954; Std. beta = -0.02, 95% CI [-0.60, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.53) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.03 (95% CI [57.30, 60.75], t(132) = 67.23, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.62, 95% CI [-0.82, 4.05], t(132) = 1.30, p = 0.193; Std. beta = 0.30, 95% CI [-0.15, 0.76])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.90, 1.70], t(132) = -0.11, p = 0.911; Std. beta = -0.02, 95% CI [-0.36, 0.32])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.28, 95% CI [-2.38, 2.94], t(132) = 0.21, p = 0.836; Std. beta = 0.05, 95% CI [-0.44, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 9.91e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.64 (95% CI [15.07, 16.21], t(132) = 53.75, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-0.93, 0.68], t(132) = -0.31, p = 0.755; Std. beta = -0.07, 95% CI [-0.52, 0.38])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-0.92, 0.30], t(132) = -0.99, p = 0.324; Std. beta = -0.17, 95% CI [-0.51, 0.17])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.66, 95% CI [-0.24, 1.56], t(132) = 1.43, p = 0.152; Std. beta = 0.37, 95% CI [-0.14, 0.87])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 5.49e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.44 (95% CI [11.98, 12.89], t(132) = 53.50, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.26, 95% CI [-0.90, 0.39], t(132) = -0.78, p = 0.435; Std. beta = -0.18, 95% CI [-0.62, 0.27])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.45, 0.42], t(132) = -0.08, p = 0.940; Std. beta = -0.01, 95% CI [-0.31, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.21, 95% CI [-0.43, 0.86], t(132) = 0.64, p = 0.520; Std. beta = 0.15, 95% CI [-0.30, 0.59])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 5.45e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.08 (95% CI [27.13, 29.03], t(132) = 57.98, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.38, 95% CI [-1.73, 0.96], t(132) = -0.56, p = 0.574; Std. beta = -0.13, 95% CI [-0.58, 0.32])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.29, 95% CI [-1.21, 0.63], t(132) = -0.62, p = 0.536; Std. beta = -0.10, 95% CI [-0.40, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.87, 95% CI [-0.48, 2.22], t(132) = 1.26, p = 0.208; Std. beta = 0.29, 95% CI [-0.16, 0.74])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 2.11e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.95 (95% CI [13.59, 16.30], t(132) = 21.62, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.31, 95% CI [-1.61, 2.22], t(132) = 0.31, p = 0.753; Std. beta = 0.07, 95% CI [-0.38, 0.52])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.23, 95% CI [-1.35, 0.88], t(132) = -0.41, p = 0.683; Std. beta = -0.05, 95% CI [-0.32, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.75, 1.55], t(132) = -0.12, p = 0.907; Std. beta = -0.02, 95% CI [-0.41, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 5.28e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.72 (95% CI [2.62, 4.81], t(132) = 6.66, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.51, 95% CI [-2.06, 1.03], t(132) = -0.65, p = 0.516; Std. beta = -0.15, 95% CI [-0.59, 0.29])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.73, 0.78], t(132) = 0.06, p = 0.956; Std. beta = 6.10e-03, 95% CI [-0.21, 0.22])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.10, 1.14], t(132) = 0.04, p = 0.972; Std. beta = 5.73e-03, 95% CI [-0.31, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 6.10e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.28 (95% CI [2.28, 4.28], t(132) = 6.44, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.49, 95% CI [-1.90, 0.93], t(132) = -0.68, p = 0.499; Std. beta = -0.15, 95% CI [-0.60, 0.29])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.66, 1.00], t(132) = 0.39, p = 0.694; Std. beta = 0.05, 95% CI [-0.21, 0.31])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.20, 95% CI [-1.03, 1.43], t(132) = 0.32, p = 0.751; Std. beta = 0.06, 95% CI [-0.32, 0.45])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 7.96e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.43 (95% CI [49.07, 53.78], t(132) = 42.79, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.41, 95% CI [-4.75, 1.92], t(132) = -0.83, p = 0.405; Std. beta = -0.19, 95% CI [-0.63, 0.26])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.54, 95% CI [-2.30, 1.21], t(132) = -0.60, p = 0.546; Std. beta = -0.07, 95% CI [-0.31, 0.16])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 2.31, 95% CI [-0.29, 4.91], t(132) = 1.74, p = 0.082; Std. beta = 0.31, 95% CI [-0.04, 0.66])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.62) and the part related to the fixed effects alone (marginal R2) is of 4.23e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.39 (95% CI [47.76, 53.03], t(132) = 37.47, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.18, 95% CI [-2.55, 4.90], t(132) = 0.62, p = 0.536; Std. beta = 0.14, 95% CI [-0.31, 0.60])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.18, 95% CI [-2.63, 2.28], t(132) = -0.14, p = 0.887; Std. beta = -0.02, 95% CI [-0.32, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.79, 95% CI [-4.42, 2.85], t(132) = -0.42, p = 0.671; Std. beta = -0.10, 95% CI [-0.54, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

sets

null

3

595.955

604.737

-294.978

589.955

sets

random

6

597.031

614.595

-292.516

585.031

4.924

3

0.177

setv

null

3

519.052

527.834

-256.526

513.052

setv

random

6

523.352

540.915

-255.676

511.352

1.700

3

0.637

maks

null

3

727.221

736.003

-360.611

721.221

maks

random

6

731.059

748.623

-359.530

719.059

2.162

3

0.540

ibs

null

3

575.644

584.426

-284.822

569.644

ibs

random

6

579.482

597.045

-283.741

567.482

2.162

3

0.539

ers_e

null

3

458.461

467.243

-226.231

452.461

ers_e

random

6

456.524

474.087

-222.262

444.524

7.937

3

0.047

ers_r

null

3

486.880

495.661

-240.440

480.880

ers_r

random

6

491.391

508.954

-239.695

479.391

1.489

3

0.685

pss_pa

null

3

805.145

813.927

-399.572

799.145

pss_pa

random

6

803.952

821.516

-395.976

791.952

7.192

3

0.066

pss_ps

null

3

920.411

929.193

-457.206

914.411

pss_ps

random

6

921.690

939.253

-454.845

909.690

4.721

3

0.193

pss

null

3

1,030.376

1,039.157

-512.188

1,024.376

pss

random

6

1,030.042

1,047.606

-509.021

1,018.042

6.333

3

0.096

rki_responsible

null

3

734.931

743.713

-364.466

728.931

rki_responsible

random

6

739.958

757.521

-363.979

727.958

0.974

3

0.808

rki_nonlinear

null

3

658.451

667.233

-326.226

652.451

rki_nonlinear

random

6

662.358

679.921

-325.179

650.358

2.094

3

0.553

rki_peer

null

3

596.118

604.900

-295.059

590.118

rki_peer

random

6

601.935

619.499

-294.968

589.935

0.183

3

0.980

rki_expect

null

3

385.799

394.581

-189.900

379.799

rki_expect

random

6

384.402

401.966

-186.201

372.402

7.397

3

0.060

rki

null

3

846.880

855.662

-420.440

840.880

rki

random

6

850.392

867.956

-419.196

838.392

2.488

3

0.477

raq_possible

null

3

544.051

552.833

-269.026

538.051

raq_possible

random

6

547.810

565.374

-267.905

535.810

2.241

3

0.524

raq_difficulty

null

3

470.646

479.428

-232.323

464.646

raq_difficulty

random

6

475.620

493.183

-231.810

463.620

1.027

3

0.795

raq

null

3

674.676

683.458

-334.338

668.676

raq

random

6

678.957

696.521

-333.479

666.957

1.719

3

0.633

who

null

3

756.288

765.069

-375.144

750.288

who

random

6

761.723

779.287

-374.862

749.723

0.564

3

0.905

phq

null

3

678.814

687.596

-336.407

672.814

phq

random

6

684.341

701.905

-336.171

672.341

0.473

3

0.925

gad

null

3

673.857

682.639

-333.928

667.857

gad

random

6

678.652

696.216

-333.326

666.652

1.205

3

0.752

nb_pcs

null

3

901.724

910.506

-447.862

895.724

nb_pcs

random

6

904.034

921.598

-446.017

892.034

3.690

3

0.297

nb_mcs

null

3

952.428

961.210

-473.214

946.428

nb_mcs

random

6

957.626

975.189

-472.813

945.626

0.802

3

0.849

Post hoc analysis text

Table

outcome

time

control

treatment

between

n

estimate

within es

n

estimate

within es

p

es

sets

1st

39

19.18 ± 2.11

39

19.95 ± 2.11

0.110

-0.456

sets

2nd

33

18.86 ± 2.09

0.190

27

19.59 ± 2.07

0.211

0.176

-0.436

setv

1st

39

11.03 ± 1.70

39

11.41 ± 1.70

0.319

-0.340

setv

2nd

33

11.28 ± 1.66

-0.225

27

11.48 ± 1.62

-0.064

0.634

-0.179

maks

1st

39

44.26 ± 3.90

39

45.15 ± 3.90

0.312

-0.436

maks

2nd

33

44.30 ± 3.74

-0.021

27

45.57 ± 3.58

-0.203

0.183

-0.618

ibs

1st

39

15.62 ± 2.12

39

15.67 ± 2.12

0.915

-0.038

ibs

2nd

33

15.81 ± 2.06

-0.143

27

16.13 ± 2.00

-0.345

0.542

-0.241

ers_e

1st

39

12.33 ± 1.43

39

12.31 ± 1.43

0.937

0.033

ers_e

2nd

33

11.81 ± 1.37

0.675

27

12.29 ± 1.32

0.018

0.167

-0.624

ers_r

1st

39

11.33 ± 1.47

39

11.49 ± 1.47

0.645

-0.143

ers_r

2nd

33

11.18 ± 1.45

0.143

27

11.62 ± 1.43

-0.127

0.235

-0.413

pss_pa

1st

39

44.41 ± 4.56

39

45.69 ± 4.56

0.217

-0.383

pss_pa

2nd

33

43.12 ± 4.49

0.386

27

44.32 ± 4.42

0.411

0.301

-0.358

pss_ps

1st

39

26.51 ± 7.27

39

24.15 ± 7.27

0.155

0.505

pss_ps

2nd

33

27.67 ± 7.08

-0.248

27

24.15 ± 6.89

0.001

0.054

0.753

pss

1st

39

45.10 ± 10.86

39

41.46 ± 10.86

0.142

0.536

pss

2nd

33

47.57 ± 10.55

-0.363

27

42.79 ± 10.24

-0.196

0.079

0.702

rki_responsible

1st

39

20.82 ± 3.67

39

21.59 ± 3.67

0.357

-0.302

rki_responsible

2nd

33

20.85 ± 3.60

-0.010

27

21.29 ± 3.53

0.116

0.628

-0.176

rki_nonlinear

1st

39

13.21 ± 2.83

39

13.69 ± 2.83

0.450

-0.266

rki_nonlinear

2nd

33

12.89 ± 2.76

0.172

27

13.88 ± 2.69

-0.100

0.165

-0.538

rki_peer

1st

39

20.54 ± 2.25

39

20.44 ± 2.25

0.841

0.068

rki_peer

2nd

33

20.56 ± 2.20

-0.013

27

20.60 ± 2.15

-0.106

0.948

-0.025

rki_expect

1st

39

4.46 ± 0.96

39

4.92 ± 0.96

0.036

-0.558

rki_expect

2nd

33

4.64 ± 0.96

-0.214

27

5.08 ± 0.96

-0.193

0.075

-0.538

rki

1st

39

59.03 ± 5.48

39

60.64 ± 5.48

0.196

-0.425

rki

2nd

33

58.92 ± 5.38

0.027

27

60.82 ± 5.27

-0.047

0.172

-0.499

raq_possible

1st

39

15.64 ± 1.82

39

15.51 ± 1.82

0.756

0.099

raq_possible

2nd

33

15.33 ± 1.79

0.238

27

15.86 ± 1.75

-0.272

0.248

-0.411

raq_difficulty

1st

39

12.44 ± 1.45

39

12.18 ± 1.45

0.437

0.279

raq_difficulty

2nd

33

12.42 ± 1.41

0.018

27

12.37 ± 1.37

-0.212

0.901

0.049

raq

1st

39

28.08 ± 3.02

39

27.69 ± 3.02

0.576

0.199

raq

2nd

33

27.79 ± 2.94

0.150

27

28.27 ± 2.86

-0.301

0.521

-0.251

who

1st

39

14.95 ± 4.32

39

15.26 ± 4.32

0.754

-0.132

who

2nd

33

14.72 ± 4.15

0.100

27

14.93 ± 3.98

0.141

0.842

-0.090

phq

1st

39

3.72 ± 3.49

39

3.21 ± 3.49

0.518

0.325

phq

2nd

33

3.74 ± 3.31

-0.014

27

3.25 ± 3.13

-0.026

0.556

0.312

gad

1st

39

3.28 ± 3.19

39

2.79 ± 3.19

0.501

0.280

gad

2nd

33

3.45 ± 3.06

-0.096

27

3.16 ± 2.94

-0.210

0.711

0.166

nb_pcs

1st

39

51.43 ± 7.51

39

50.01 ± 7.51

0.408

0.385

nb_pcs

2nd

33

50.89 ± 7.17

0.147

27

51.78 ± 6.81

-0.482

0.621

-0.244

nb_mcs

1st

39

50.39 ± 8.40

39

51.57 ± 8.40

0.538

-0.228

nb_mcs

2nd

33

50.21 ± 8.15

0.034

27

50.60 ± 7.90

0.187

0.852

-0.075

Between group

sets

1st

t(120.71) = 1.61, p = 0.110, Cohen d = -0.46, 95% CI (-0.18 to 1.71)

2st

t(130.34) = 1.36, p = 0.176, Cohen d = -0.44, 95% CI (-0.33 to 1.80)

setv

1st

t(106.66) = 1.00, p = 0.319, Cohen d = -0.34, 95% CI (-0.38 to 1.15)

2st

t(123.07) = 0.48, p = 0.634, Cohen d = -0.18, 95% CI (-0.64 to 1.04)

maks

1st

t(94.30) = 1.02, p = 0.312, Cohen d = -0.44, 95% CI (-0.86 to 2.65)

2st

t(111.18) = 1.34, p = 0.183, Cohen d = -0.62, 95% CI (-0.61 to 3.15)

ibs

1st

t(103.01) = 0.11, p = 0.915, Cohen d = -0.04, 95% CI (-0.90 to 1.00)

2st

t(120.25) = 0.61, p = 0.542, Cohen d = -0.24, 95% CI (-0.72 to 1.36)

ers_e

1st

t(95.55) = -0.08, p = 0.937, Cohen d = 0.03, 95% CI (-0.67 to 0.62)

2st

t(112.71) = 1.39, p = 0.167, Cohen d = -0.62, 95% CI (-0.21 to 1.17)

ers_r

1st

t(113.44) = 0.46, p = 0.645, Cohen d = -0.14, 95% CI (-0.51 to 0.81)

2st

t(127.17) = 1.19, p = 0.235, Cohen d = -0.41, 95% CI (-0.29 to 1.18)

pss_pa

1st

t(113.64) = 1.24, p = 0.217, Cohen d = -0.38, 95% CI (-0.76 to 3.33)

2st

t(127.27) = 1.04, p = 0.301, Cohen d = -0.36, 95% CI (-1.09 to 3.49)

pss_ps

1st

t(104.26) = -1.43, p = 0.155, Cohen d = 0.51, 95% CI (-5.62 to 0.91)

2st

t(121.27) = -1.94, p = 0.054, Cohen d = 0.75, 95% CI (-7.10 to 0.07)

pss

1st

t(102.66) = -1.48, p = 0.142, Cohen d = 0.54, 95% CI (-8.52 to 1.24)

2st

t(119.95) = -1.77, p = 0.079, Cohen d = 0.70, 95% CI (-10.11 to 0.56)

rki_responsible

1st

t(109.40) = 0.92, p = 0.357, Cohen d = -0.30, 95% CI (-0.88 to 2.42)

2st

t(124.88) = 0.49, p = 0.628, Cohen d = -0.18, 95% CI (-1.38 to 2.28)

rki_nonlinear

1st

t(104.69) = 0.76, p = 0.450, Cohen d = -0.27, 95% CI (-0.79 to 1.76)

2st

t(121.61) = 1.40, p = 0.165, Cohen d = -0.54, 95% CI (-0.41 to 2.38)

rki_peer

1st

t(106.76) = -0.20, p = 0.841, Cohen d = 0.07, 95% CI (-1.11 to 0.91)

2st

t(123.14) = 0.07, p = 0.948, Cohen d = -0.02, 95% CI (-1.08 to 1.15)

rki_expect

1st

t(126.68) = 2.12, p = 0.036, Cohen d = -0.56, 95% CI (0.03 to 0.89)

2st

t(132.26) = 1.79, p = 0.075, Cohen d = -0.54, 95% CI (-0.05 to 0.94)

rki

1st

t(109.39) = 1.30, p = 0.196, Cohen d = -0.42, 95% CI (-0.85 to 4.08)

2st

t(124.88) = 1.37, p = 0.172, Cohen d = -0.50, 95% CI (-0.83 to 4.63)

raq_possible

1st

t(111.39) = -0.31, p = 0.756, Cohen d = 0.10, 95% CI (-0.94 to 0.69)

2st

t(126.07) = 1.16, p = 0.248, Cohen d = -0.41, 95% CI (-0.38 to 1.44)

raq_difficulty

1st

t(103.27) = -0.78, p = 0.437, Cohen d = 0.28, 95% CI (-0.91 to 0.40)

2st

t(120.46) = -0.12, p = 0.901, Cohen d = 0.05, 95% CI (-0.76 to 0.67)

raq

1st

t(103.80) = -0.56, p = 0.576, Cohen d = 0.20, 95% CI (-1.74 to 0.97)

2st

t(120.90) = 0.64, p = 0.521, Cohen d = -0.25, 95% CI (-1.01 to 1.97)

who

1st

t(95.35) = 0.31, p = 0.754, Cohen d = -0.13, 95% CI (-1.63 to 2.25)

2st

t(112.47) = 0.20, p = 0.842, Cohen d = -0.09, 95% CI (-1.88 to 2.30)

phq

1st

t(89.11) = -0.65, p = 0.518, Cohen d = 0.32, 95% CI (-2.08 to 1.06)

2st

t(103.74) = -0.59, p = 0.556, Cohen d = 0.31, 95% CI (-2.15 to 1.16)

gad

1st

t(95.74) = -0.68, p = 0.501, Cohen d = 0.28, 95% CI (-1.92 to 0.94)

2st

t(112.94) = -0.37, p = 0.711, Cohen d = 0.17, 95% CI (-1.83 to 1.25)

nb_pcs

1st

t(91.48) = -0.83, p = 0.408, Cohen d = 0.39, 95% CI (-4.79 to 1.96)

2st

t(107.35) = 0.50, p = 0.621, Cohen d = -0.24, 95% CI (-2.69 to 4.48)

nb_mcs

1st

t(101.67) = 0.62, p = 0.538, Cohen d = -0.23, 95% CI (-2.60 to 4.95)

2st

t(119.09) = 0.19, p = 0.852, Cohen d = -0.08, 95% CI (-3.73 to 4.51)

Within treatment group

sets

1st vs 2st

t(69.82) = -0.81, p = 0.419, Cohen d = 0.21, 95% CI (-1.23 to 0.52)

setv

1st vs 2st

t(66.24) = 0.24, p = 0.808, Cohen d = -0.06, 95% CI (-0.52 to 0.67)

maks

1st vs 2st

t(63.12) = 0.76, p = 0.450, Cohen d = -0.20, 95% CI (-0.68 to 1.51)

ibs

1st vs 2st

t(65.33) = 1.31, p = 0.196, Cohen d = -0.35, 95% CI (-0.24 to 1.16)

ers_e

1st vs 2st

t(63.44) = -0.07, p = 0.945, Cohen d = 0.02, 95% CI (-0.43 to 0.40)

ers_r

1st vs 2st

t(67.93) = 0.49, p = 0.628, Cohen d = -0.13, 95% CI (-0.42 to 0.70)

pss_pa

1st vs 2st

t(67.98) = -1.57, p = 0.121, Cohen d = 0.41, 95% CI (-3.12 to 0.37)

pss_ps

1st vs 2st

t(65.64) = -0.00, p = 0.998, Cohen d = 0.00, 95% CI (-2.47 to 2.46)

pss

1st vs 2st

t(65.24) = 0.74, p = 0.461, Cohen d = -0.20, 95% CI (-2.26 to 4.92)

rki_responsible

1st vs 2st

t(66.92) = -0.44, p = 0.661, Cohen d = 0.12, 95% CI (-1.63 to 1.04)

rki_nonlinear

1st vs 2st

t(65.75) = 0.38, p = 0.707, Cohen d = -0.10, 95% CI (-0.78 to 1.15)

rki_peer

1st vs 2st

t(66.26) = 0.40, p = 0.689, Cohen d = -0.11, 95% CI (-0.63 to 0.95)

rki_expect

1st vs 2st

t(71.57) = 0.75, p = 0.455, Cohen d = -0.19, 95% CI (-0.26 to 0.58)

rki

1st vs 2st

t(66.91) = 0.18, p = 0.860, Cohen d = -0.05, 95% CI (-1.82 to 2.17)

raq_possible

1st vs 2st

t(67.41) = 1.04, p = 0.303, Cohen d = -0.27, 95% CI (-0.33 to 1.03)

raq_difficulty

1st vs 2st

t(65.39) = 0.80, p = 0.425, Cohen d = -0.21, 95% CI (-0.29 to 0.68)

raq

1st vs 2st

t(65.53) = 1.14, p = 0.260, Cohen d = -0.30, 95% CI (-0.44 to 1.60)

who

1st vs 2st

t(63.39) = -0.53, p = 0.598, Cohen d = 0.14, 95% CI (-1.58 to 0.91)

phq

1st vs 2st

t(61.75) = 0.10, p = 0.922, Cohen d = -0.03, 95% CI (-0.81 to 0.89)

gad

1st vs 2st

t(63.49) = 0.79, p = 0.434, Cohen d = -0.21, 95% CI (-0.56 to 1.29)

nb_pcs

1st vs 2st

t(62.38) = 1.80, p = 0.076, Cohen d = -0.48, 95% CI (-0.19 to 3.73)

nb_mcs

1st vs 2st

t(64.99) = -0.70, p = 0.484, Cohen d = 0.19, 95% CI (-3.70 to 1.77)

Within control group

sets

1st vs 2st

t(64.25) = -0.79, p = 0.432, Cohen d = 0.19, 95% CI (-1.13 to 0.49)

setv

1st vs 2st

t(62.24) = 0.93, p = 0.357, Cohen d = -0.22, 95% CI (-0.29 to 0.80)

maks

1st vs 2st

t(60.60) = 0.09, p = 0.932, Cohen d = -0.02, 95% CI (-0.96 to 1.05)

ibs

1st vs 2st

t(61.76) = 0.59, p = 0.559, Cohen d = -0.14, 95% CI (-0.46 to 0.84)

ers_e

1st vs 2st

t(60.76) = -2.77, p = 0.007, Cohen d = 0.68, 95% CI (-0.90 to -0.15)

ers_r

1st vs 2st

t(63.17) = -0.59, p = 0.556, Cohen d = 0.14, 95% CI (-0.67 to 0.37)

pss_pa

1st vs 2st

t(63.20) = -1.60, p = 0.114, Cohen d = 0.39, 95% CI (-2.91 to 0.32)

pss_ps

1st vs 2st

t(61.92) = 1.02, p = 0.311, Cohen d = -0.25, 95% CI (-1.11 to 3.42)

pss

1st vs 2st

t(61.71) = 1.49, p = 0.140, Cohen d = -0.36, 95% CI (-0.83 to 5.76)

rki_responsible

1st vs 2st

t(62.61) = 0.04, p = 0.967, Cohen d = -0.01, 95% CI (-1.21 to 1.26)

rki_nonlinear

1st vs 2st

t(61.98) = -0.71, p = 0.481, Cohen d = 0.17, 95% CI (-1.20 to 0.57)

rki_peer

1st vs 2st

t(62.25) = 0.05, p = 0.957, Cohen d = -0.01, 95% CI (-0.71 to 0.75)

rki_expect

1st vs 2st

t(65.29) = 0.89, p = 0.376, Cohen d = -0.21, 95% CI (-0.22 to 0.57)

rki

1st vs 2st

t(62.61) = -0.11, p = 0.911, Cohen d = 0.03, 95% CI (-1.94 to 1.74)

raq_possible

1st vs 2st

t(62.88) = -0.98, p = 0.328, Cohen d = 0.24, 95% CI (-0.93 to 0.32)

raq_difficulty

1st vs 2st

t(61.79) = -0.08, p = 0.940, Cohen d = 0.02, 95% CI (-0.46 to 0.43)

raq

1st vs 2st

t(61.86) = -0.62, p = 0.539, Cohen d = 0.15, 95% CI (-1.22 to 0.65)

who

1st vs 2st

t(60.74) = -0.41, p = 0.684, Cohen d = 0.10, 95% CI (-1.37 to 0.91)

phq

1st vs 2st

t(59.89) = 0.06, p = 0.956, Cohen d = -0.01, 95% CI (-0.75 to 0.79)

gad

1st vs 2st

t(60.79) = 0.39, p = 0.696, Cohen d = -0.10, 95% CI (-0.68 to 1.01)

nb_pcs

1st vs 2st

t(60.22) = -0.60, p = 0.548, Cohen d = 0.15, 95% CI (-2.33 to 1.25)

nb_mcs

1st vs 2st

t(61.58) = -0.14, p = 0.888, Cohen d = 0.03, 95% CI (-2.69 to 2.33)

Plot